Significance Testing: We Can Do Better.
This paper advocates abandoning null hypothesis statistical tests (NHST) in favour of reporting confidence intervals. The case against NHST, which has been made repeatedly in multiple disciplines and is growing in awareness and acceptance, is introduced and discussed. Accounting as an empirical rese...
| Publicado en: | Abacus Vol. 52; no. 2; pp. 319 - 343 |
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| Formato: | Artículo |
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Wiley-Blackwell
Jun2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=116102063&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 116102063 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00013072 AUB jtl: Abacus issn: 00013072 maglogo: Y pubinfo: dt: Jun2016 vid: 52 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 116102063 10.1111/abac.12078 ppf: 319 ppct: 24 formats: fmt: – @attributes: type: T – @attributes: type: P size: 294KB tig: atl: Significance Testing: We Can Do Better. aug: au: Dyckman, Thomas R. affil: Cornell University and Adjunct Professor at Florida Gulf Coast University su: Statistical hypothesis testing Null hypothesis Confidence intervals Empirical research Test interpretation sug: subj: Statistical hypothesis testing Null hypothesis Confidence intervals Empirical research Test interpretation keyword: Bayesian Confidence interval reporting Frequentist Meta‐analysis Meta-analysis ab: This paper advocates abandoning null hypothesis statistical tests (NHST) in favour of reporting confidence intervals. The case against NHST, which has been made repeatedly in multiple disciplines and is growing in awareness and acceptance, is introduced and discussed. Accounting as an empirical research discipline appears to be the last of the research communities to face up to the inherent problems of significance test use and abuse. The paper encourages adoption of a meta-analysis approach which allows for the inclusion of replication studies in the assessment of evidence. This approach requires abandoning the typical NHST process and its reliance on p-values. However, given that NHST has deep roots and wide 'social acceptance' in the empirical testing community, modifications to NHST are suggested so as to partly counter the weakness of this statistical testing method. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Abacus is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Abacus holder: Wiley-Blackwell dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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